Dating with Scambots: Understanding the Ecosystem of Fraudulent Dating Applications
Yangyu Hu, Haoyu Wang, Yajin Zhou, Yao Guo, Li Li, Bingxuan Luo and, Fangren Xu

TL;DR
This paper systematically studies fraudulent dating apps that deceive users into purchasing premium services, revealing their ecosystem, chatbot-based profiles, and significant financial impact, highlighting the need for protective solutions.
Contribution
It introduces a three-phase detection method and provides the first comprehensive analysis of the ecosystem, profiles, and business models of fraudulent dating apps.
Findings
Most accounts are chatbots, not real persons.
Multiple parties are involved in the ecosystem.
Estimated significant revenue generated by these apps.
Abstract
In this work, we are focusing on a new and yet uncovered way for malicious apps to gain profit. They claim to be dating apps. However, their sole purpose is to lure users into purchasing premium/VIP services to start conversations with other (likely fake female) accounts in the app. We call these apps as fraudulent dating apps. This paper performs a systematic study to understand the whole ecosystem of fraudulent dating apps. Specifically, we have proposed a three-phase method to detect them and subsequently comprehend their characteristics via analyzing the existing account profiles. Our observation reveals that most of the accounts are not managed by real persons, but by chatbots based on predefined conversation templates. We also analyze the business model of these apps and reveal that multiple parties are actually involved in the ecosystem, including producers who develop apps,…
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Taxonomy
TopicsAdvanced Malware Detection Techniques · Spam and Phishing Detection · Cybercrime and Law Enforcement Studies
